Learn how to implement classification using decision trees in R through this comprehensive tutorial. Explore the fundamentals of classification and decision tree learning, including their advantages and applications. Dive into a gold loan case study to gain practical insights. Delve deep into decision tree concepts, understanding Gini index, entropy, and misclassification error. Master the art of measuring impurity and discover various types of decision tree algorithms. Gain hands-on experience with demonstrations and examples to solidify your understanding of tree-based models for classification tasks.
Overview
Syllabus
➤ Skip Intro: .
Introduction.
What is Classification?.
What is Decision Tree Learning?.
Advantages of using Tree-based Models.
Gold Loan Case Study.
Decision Tree in-depth Concept.
Gini Index, Entropy, Misclassification Error.
Measuring Impurity.
Types of Decision Tree algorithms.
Taught by
Great Learning
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